ROSDiscover:机器人系统中静态检测运行时架构错误配置

C. Timperley, Tobias Dürschmid, B. Schmerl, D. Garlan, Claire Le Goues
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引用次数: 4

摘要

机器人系统的重要性和复杂性都在增长。机器人软件的生态系统,如机器人操作系统(ROS),提供了可重用的软件组件库,这些组件可以配置和组成更大的系统。为了支持组合性,ROS通过描述如何初始化系统中的组件的“启动文件”使用后期绑定和体系结构配置。但是,延迟绑定通常会导致系统由于错误配置而静默失败,例如错误路由或完全丢弃消息。在本文中,我们提出了ROSDiscover,它静态地恢复ROS系统的运行时架构,以发现此类架构错误配置错误。首先,ROSDiscover从源代码构造组件级体系结构模型(端口、参数)。其次,分析体系结构配置文件,从这些组件模型组成系统,并推导出系统中的连接。最后,根据一阶逻辑中描述的体系结构规则检查重构的体系结构,以识别潜在的错误配置。我们在真实世界的现成机器人系统上对ROSDiscover进行了评估,测量了我们方法的准确性、有效性和实用性。为此,我们从流行的开源系统中收集了ROS中的架构配置错误的第一个数据集,并测量了我们的方法在该数据集中检测配置错误的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
ROSDiscover: Statically Detecting Run-Time Architecture Misconfigurations in Robotics Systems
Robot systems are growing in importance and complexity. Ecosystems for robot software, such as the Robot Operating System (ROS), provide libraries of reusable software components that can be configured and composed into larger systems. To support compositionality, ROS uses late binding and architecture configuration via “launch files” that describe how to initialize the components in a system. However, late binding often leads to systems failing silently due to misconfiguration, for example by misrouting or dropping messages entirely.In this paper we present ROSDiscover, which statically recovers the run-time architecture of ROS systems to find such architecture misconfiguration bugs. First, ROSDiscover constructs component level architectural models (ports, parameters) from source code. Second, architecture configuration files are analyzed to compose the system from these component models and derive the connections in the system. Finally, the reconstructed architecture is checked against architectural rules described in first-order logic to identify potential misconfigurations.We present an evaluation of ROSDiscover on real world, off-the-shelf robotic systems, measuring the accuracy, effectiveness, and practicality of our approach. To that end, we collected the first data set of architecture configuration bugs in ROS from popular open-source systems and measure how effective our approach is for detecting configuration bugs in that set.
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